AIMC Topic: Humans

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Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution.

Environmental health : a global access science source
BACKGROUND: Air pollution epidemiology has primarily relied on measurements from fixed outdoor air quality monitoring stations to derive population-scale exposure. Characterisation of individual time-activity-location patterns is critical for accurat...

A Machine Learning Model for Prediction of Amputation in Diabetics.

Journal of diabetes science and technology
BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated with a poor survival prognosis. The objective of this study is to generate a model for predicting the probability of major amputation in hospitalized pa...

Impact of deep learning image reconstructions (DLIR) on coronary artery calcium quantification.

European radiology
BACKGROUND: Deep learning image reconstructions (DLIR) have been recently introduced as an alternative to filtered back projection (FBP) and iterative reconstruction (IR) algorithms for computed tomography (CT) image reconstruction. The aim of this s...

Improving accelerated MRI by deep learning with sparsified complex data.

Magnetic resonance in medicine
PURPOSE: To obtain high-quality accelerated MR images with complex-valued reconstruction from undersampled k-space data.

Self-regulated learning and the future of diagnostic reasoning education.

Diagnosis (Berlin, Germany)
Diagnostic reasoning is a foundational ability of health professionals. The goal of enhancing clinical reasoning education is improved diagnostic accuracy and reduced diagnostic error. In order to do so, health professions educators need not only hel...

Artificial Intelligence and Machine Learning in Perioperative Acute Kidney Injury.

Advances in kidney disease and health
Acute kidney injury (AKI) is a common complication after a surgery, especially in cardiac and aortic procedures, and has a significant impact on morbidity and mortality. Early identification of high-risk patients and providing effective prevention an...

Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning.

IEEE journal of translational engineering in health and medicine
OBJECTIVE: Early revascularization of the occluded coronary artery in patients with ST elevation myocardial infarction (STEMI) has been demonstrated to decrease mortality and morbidity. Currently, physicians rely on features of electrocardiograms (EC...

Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Methods in enzymology
Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray...